The Impact of Expectation Management and Model Transparency on Radiologists' Trust and Utilization of AI Recommendations for Lung Nodule Assessment on Computed Tomography: Simulated Use Study.

BACKGROUND: Many promising artificial intelligence (AI) and computer-aided detection and diagnosis systems have been developed, but few have been successfully integrated into clinical practice. This is partially owing to a lack of user-centered design of AI-based computer-aided detection or diagnosis (AI-CAD) systems. OBJECTIVE: We aimed to assess the impact of different onboarding tutorials and levels of AI model explainability on radiologists' trust in AI and the use of AI recommendations in lung nodule assessment on computed tomography (CT) scans. METHODS: In total, 20 radiologists from 7 Dutch medical centers performed lung nodule assessment on CT scans under different conditions in a simulated use study as part of a 2×2 repeated-measures quasi-experimental design. Two types of AI onboarding tutorials (reflective vs informative) and 2 levels of AI output (black box vs explainable) were designed. The radiologists first received an onboarding tutorial that was either informative or reflective. Subsequently, each radiologist assessed 7 CT scans, first without AI recommendations. AI recommendations were shown to the radiologist, and they could adjust their initial assessment. Half of the participants received the recommendations via black box AI output and half received explainable AI output. Mental model and psychological trust were measured before onboarding, after onboarding, and after assessing the 7 CT scans. We recorded whether radiologists changed their assessment on found nodules, malignancy prediction, and follow-up advice for each CT assessment. In addition, we analyzed whether radiologists' trust in their assessments had changed based on the AI recommendations. RESULTS: Both variations of onboarding tutorials resulted in a significantly improved mental model of the AI-CAD system (informative P=.01 and reflective P=.01). After using AI-CAD, psychological trust significantly decreased for the group with explainable AI output (P=.02). On the basis of the AI recommendations, radiologists changed the number of reported nodules in 27 of 140 assessments, malignancy prediction in 32 of 140 assessments, and follow-up advice in 12 of 140 assessments. The changes were mostly an increased number of reported nodules, a higher estimated probability of malignancy, and earlier follow-up. The radiologists' confidence in their found nodules changed in 82 of 140 assessments, in their estimated probability of malignancy in 50 of 140 assessments, and in their follow-up advice in 28 of 140 assessments. These changes were predominantly increases in confidence. The number of changed assessments and radiologists' confidence did not significantly differ between the groups that received different onboarding tutorials and AI outputs. CONCLUSIONS: Onboarding tutorials help radiologists gain a better understanding of AI-CAD and facilitate the formation of a correct mental model. If AI explanations do not consistently substantiate the probability of malignancy across patient cases, radiologists' trust in the AI-CAD system can be impaired. Radiologists' confidence in their assessments was improved by using the AI recommendations.

Protocol for an interview-based method for mapping mental models using causal-loop diagramming and realist interviewing.

Causal-loop diagramming, a method from system dynamics, is increasingly used in evaluation to describe individuals' understanding of how policies or programs do or could work ("mental models"). The use of qualitative interviews to inform model development is common, but guidance for how to design and conduct these interviews to elicit causal information in participant mental models is scant. A key strength of semi-structured qualitative interviews is that they let participants speak freely; they are not, however, designed to elicit causal information. Moreover, much of human communication about mental models-particularly larger causal structures such as feedback loops-is implicit. In qualitative research, part of the skill and art of effective interviewing and analysis involves listening for information that is expressed implicitly. Similarly, a skilled facilitator can recognize and inquire about implied causal structures, as is commonly done in group model building. To standardize and make accessible these approaches, we have formalized a protocol for designing and conducting semi-structured interviews tailored to eliciting mental models using causal-loop diagramming. We build on qualitative research methods, system dynamics, and realist interviewing. This novel, integrative method is designed to increase transparency and rigor in the use of interviews for system dynamics and has a variety of potential applications.

Exploring Dynamics of Water, Energy, and Food Systems in Agricultural Landscapes Using Mental Modeling: A Case of Varamin Plain, Iran.

This study applies the mental model and cognitive mapping method to involve stakeholders in delineating the mutual relations between sources of water, energy, and food (WEF) production in the Varamin Plain (VP). Through involving farmers and managerial experts, the approach facilitates the deployment of community communication patterns to recognize and comprehend problems and move from single-loop learning to double-loop learning. The dynamic model was driven from the final mental model of the participants to reflect changes in the systems over time. The system dynamic (SD) model incorporates three scenarios for enhancing irrigation efficiency, managing groundwater extraction, and satisfying environmental needs. The results uncovered that the surface and underground water resources of the VP will gradually decrease within the next two decades in the range of 158 and 2700 million cubic meters (MCM) per year. Also, the plain suffers from water insecurity and a 162 MCM shortage. Consequently, focusing on understanding the nexus and nexus governance can enhance resource management and achieve sustainable development goals. Essentially, promoting collaborative governance, such as creating cooperative organizations and implementing double-loop learning, and instituting a water market, regulatory governance, and monitoring laws can improve the state of Varamin Plain's resources. These results carry important policy implications for using mental models to consider dynamics for discussions on participatory management of the WEF system nexus and environmental management.

On the edge of decision-making in trauma care: A focus group study on radiographers' experiences of interprofessional collaboration.

INTRODUCTION: The temporary trauma teams in trauma alerts consist of a diverse group of unique professionals requiring interprofessional collaboration and coordination to achieve efficient, high-quality care. The uncertain situation and complex care environment impose high demands on team dynamics such as individual attitudes and team behaviours. Within interprofessional teams, interaction and coordination reflect the collective success of collaboration and the achievement of goals. Interactions with radiographers have increased in trauma teams given computed tomography's prominent role in providing crucial knowledge for decision-making in trauma care. This study aimed to explore radiographers' experiences of interprofessional collaboration during trauma alerts. METHOD: The study was designed with focus group methodology, including 17 radiographers participating in five focus groups, analysed with an inductive focus group analysis. RESULTS: An overarching theme, "On the edge of decision-making", emerged along with three sub-themes: "Feeling included requires acknowledgement", "Exclusion precludes shared knowledge", and "Experience and mutual awareness facilitate team interaction". CONCLUSIONS: Interprofessional collaboration from the radiographer's perspective within trauma teams requires a sense of inclusion and the ability to interact with the team. Exclusion from vital decision-making obstructs radiographers' comprehension of situations and thereby the interdependence in interprofessional collaboration. IMPLICATIONS FOR PRACTICE: Common platforms are needed for knowledge sharing and team practices, including radiographers' areas of responsibility and relational coordination to foster interprofessional relationships. Through these means interdependence through awareness and shared knowledge can be facilitated on trauma teams.

Exploring the effect of automation failure on the human's trustworthiness in human-agent teamwork.

Introduction: Collaboration in teams composed of both humans and automation has an interdependent nature, which demands calibrated trust among all the team members. For building suitable autonomous teammates, we need to study how trust and trustworthiness function in such teams. In particular, automation occasionally fails to do its job, which leads to a decrease in a human's trust. Research has found interesting effects of such a reduction of trust on the human's trustworthiness, i.e., human characteristics that make them more or less reliable. This paper investigates how automation failure in a human-automation collaborative scenario affects the human's trust in the automation, as well as a human's trustworthiness towards the automation. Methods: We present a 2 × 2 mixed design experiment in which the participants perform a simulated task in a 2D grid-world, collaborating with an automation in a "moving-out" scenario. During the experiment, we measure the participants' trustworthiness, trust, and liking regarding the automation, both subjectively and objectively. Results: Our results show that automation failure negatively affects the human's trustworthiness, as well as their trust in and liking of the automation. Discussion: Learning the effects of automation failure in trust and trustworthiness can contribute to a better understanding of the nature and dynamics of trust in these teams and improving human-automation teamwork.

Teamwork makes the dream work: Testing for shared perceptions on psycho-behavioural skills between athletes, coaches and parents.

Psycho-behavioural skills play a key role in optimising progression through talent development, and this study investigated to what extent athlete's self-perceptions align with those of their coaches and parents. Firstly, we examined if levels of alignment between these three raters differ across age of the athlete. To this end, 122 athletes between 9 and 18 years old (12.17 ± 2.41 years old; 47 gymnasts, 13 cyclists and 62 badminton players) completed a psycho-behavioural questionnaire. The ANOVA's indicated low levels of correspondence between the ratings of the athlete, the coach and the parents during childhood, while better levels of shared perceptions were found in adolescence. Secondly, we investigated to what extent coaches and parents believed their own perception of the athlete's and the perception of the athlete's psycho-behavioural skills were accurate. Parents appeared to be more confident in accurately perceiving the psycho-behavioural skills of the athlete than coaches. Parents and coaches also believed that older athletes would be more honest on their psycho-behavioural shortcomings than younger athletes. Altogether, these findings highlight that athletes and other stakeholders in the talent development environment should strive for better alignment in perceptions on psycho-behavioural skills during the talent development pathway. With better integrated perceptions, a more functional and efficient talent development system for the athlete targeting the psycho-behavioural skills can be created.

Using social-ecological models to explore stream connectivity outcomes for stakeholders and Yellowstone cutthroat trout.

Despite growing interest in conservation and re-establishment of ecological connectivity, few studies have explored its context-specific social-ecological outcomes. We aimed to explore social and ecological outcomes to changing stream connectivity for both stakeholders and native fish species impacted by habitat fragmentation and nonnative species. We (1) investigated stakeholder perceptions of the drivers and outcomes of stream connectivity, and (2) evaluated the effects of stakeholder-identified connectivity and nonnative species scenarios on Yellowstone cutthroat trout (YCT) populations. Our study was conducted in the Teton River, Idaho, USA. We integrated two modeling approaches, mental modeling and individual-based ecological modeling, to explore social-ecological outcomes for stakeholders and YCT populations. Aggregation of mental models revealed an emergent pattern of increasing complexity as more types of stakeholders were considered, as well as gaps and linkages among different stakeholder knowledge areas. These results highlight the importance of knowledge sharing among stakeholders when making decisions about connectivity. Additionally, the results from the individual-based models suggested that the potential for a large, migratory life history form of YCT, in addition to self-preference mating where they overlap with rainbow trout, had the strongest effects on outcomes for YCT. Exploring social and ecological drivers and outcomes to changing connectivity is useful for anticipating and adapting to unintended outcomes, as well as making decisions for desirable outcomes. The results from this study can contribute to the management dialogue surrounding stream connectivity in the Teton River, as well as to our understanding of connectivity conservation and its outcomes more broadly.

Imagery, emotion, and bioinformational theory: From body to brain.

The bioinformational theory of emotional imagery is a model of the hypothetical mental representations activated when people imagine emotionally engaging events, and was initially proposed to guide research and practice in the use of imaginal exposure as a treatment for fear and anxiety (Lang, 1979). In this 50 year overview, we discuss the development of bioinformational theory and its impact on the study of psychophysiology and psychopathology, most importantly assessing its viability and predictions in light of more recent brain-based studies of neural functional activation. Bioinformational theory proposes that narrative imagery, typically cued by language scripts, activates an associative memory network in the brain that includes stimulus (e.g., agents, contexts), semantic (e.g., facts and beliefs) and, most critically for emotion, response information (e.g., autonomic and somatic) that represents relevant real-world coping actions and reactions. Psychophysiological studies in healthy and clinical samples reliably find measurable response output during aversive and appetitive narrative imagery. Neuroimaging studies confirm that emotional imagery is associated with significant activation in motor regions of the brain, as well as in regions implicated in episodic and semantic memory retrieval, supporting the bioinformational view that narrative imagery prompts mental simulation of events that critically includes the actions and reactions engaged in emotional contexts.

Beyond adaptive cruise control and lane centering control: drivers' mental model of and trust in emerging ADAS technologies.

Introduction: The potential safety benefits of advanced driver assistance systems (ADAS) highly rely on drivers' appropriate mental models of and trust in ADAS. Current research mainly focused on drivers' mental model of adaptive cruise control (ACC) and lane centering control (LCC), but rarely investigated drivers' understanding of emerging driving automation functions beyond ACC and LCC. Methods: To address this research gap, 287 valid responses from ADAS users in the Chinese market, were collected in a survey study targeted toward state-of-the-art ADAS (e.g., autopilot in Tesla). Through cluster analysis, drivers were clustered into four groups based on their knowledge of traditional ACC and LCC functions, knowledge of functions beyond ACC and LCC, and knowledge of ADAS limitations. Predictors of driver grouping were analyzed, and we further modeled drivers' trust in ADAS. Results: Drivers in general had weak knowledge of LCC functions and functions beyond ACC and LCC, and only 27 (9%) of respondents had a relatively strong mental model of ACC and LCC. At the same time, years of licensure, weekly driving distance, ADAS familiarity, driving style (i.e., planning), and personability (i.e., agreeableness) were associated with drivers' mental model of ADAS. Further, it was found that the mental model of ADAS, vehicle brand, and drivers' age, ADAS experience, driving style (i.e., focus), and personality (i.e., emotional stability) were significant predictors of drivers' trust in ADAS. Discussion: These findings provide valuable insights for the design of driver education and training programs to improve driving safety with ADAS.

Analyzing and supporting mental representations and strategies in solving Bayesian problems.

Solving Bayesian problems poses many challenges, such as identifying relevant numerical information, classifying, and translating it into mathematical formula language, and forming a mental representation. This triggers research on how to support the solving of Bayesian problems. The facilitating effect of using numerical data in frequency format instead of probabilities is well documented, as is the facilitating effect of given visualizations of statistical data. The present study not only compares the visualizations of the 2 × 2 table and the unit square, but also focuses on the results obtained from the self-creation of these visualizations by the participants. Since it has not yet been investigated whether the better correspondence between external and internal visualization also has an effect on cognitive load when solving Bayesian tasks, passive and active cognitive load are additionally measured. Due to the analog character and the proportional representation of the numerical information by the unit square, it is assumed that the passive cognitive load is lower when using the unit square as visualization than when using the 2 × 2 table. The opposite is true for active cognitive load.

Team Strategies and Dynamics During Resuscitation.

Resuscitations are complex events that require teamwork to succeed. In addition to the technical skills involved, a host of nontechnical skills are critical for optimal medical care delivery. These skills include mental preparation; planning for tasks and roles; leadership to guide resuscitation progress; and clear, closed-loop communication. Concerns and error detection should be escalated in an established format. Debriefing after the event helps identify learning points to carry forward for the next resuscitation. Support of the team providing this intense form of care is crucial to protect the mental health and function of providers.

The Path Toward Fellow Designation in the Academy of Emergency Nursing: Understanding and Navigating the Process to Ensure Your Success.

The Academy of Emergency Nursing was established to honor emergency nurses who have made enduring and substantial contributions that have had significant impact and continue to advance the emergency nursing specialty. Nurses who have been recognized as having made enduring and substantial contributions to emergency nursing achieve fellow status in the Academy of Emergency Nursing and are conferred the credential, Fellow of the Academy of Emergency Nursing. Academy of Emergency Nursing Board Members want to dismantle any structural barriers, clarify any misunderstandings or mysteries, and support diverse candidates by providing clear and equitable resources about the path toward fellow designation and the application process. Therefore, the purpose of this article is to support interested persons in their path toward Academy of Emergency Nursing fellow designation and give explicit details of each section of the application to develop a shared understanding among potential applicants, sponsors, and Fellows of the Academy of Emergency Nursing.

Healthcare is not about health.

Initiatives designed to reduce the disease burden and improve the health of the US population that focus on increasing access to health care have been disappointing. Progress requires multifaceted change. We must first acknowledge that the healthcare system is focused on reversing or modifying disease, not enhancing health. Our conceptualization of the development of ill health and disease must also change. Scientific advances are clarifying the complex interactions among the development of ill health and disease and an individual's behaviors, their microbiota, and their physical, social, and emotional environments. A person's genetic makeup predisposes them to a wide array of disease conditions but is rarely deterministic in and of itself. Factors extrinsic to the individual, including the social determinants of health, play a major role in disease development, often decades later. The complexity of health and disease requires a "team" accountable for the health of our populations, and these teams must be expanded beyond the medical professions. Governmental officials, architects, business leaders, civic organizations, social and neighborhood groups are among the key stakeholders on the health side of the equation. If and when disease does become manifest, then the care part of the healthcare system assumes the larger role. This has major implications for the education of our clinically focused health science students, but also of professional disciplines previously deemed peripheral to health. Simply redoubling our efforts and focusing on our current healthcare system is insufficient to make progress in the health of the populace. One example of a multipronged approach in Allentown, PA is explored in depth.

Temporal development of high-performance translational teams.

Successful translation involves the coupled application of knowledge-generating research with product development to advance a device, drug, diagnostic, or evidence-based intervention for clinical adoption to improve human health. Critical to the success of the CTSA consortium, translation can be more effectively accomplished by training approaches that focus on improving team-emergent knowledge skills and attitudes (KSAs) linked to performance. We earlier identified 15 specific evidence-informed, team-emergent competencies that facilitate translational team (TT) performance. Here, we examine the SciTS literature describing developmental, temporal dynamics, and adaptive learning stages of interdisciplinary teams and integrate these with real-world observations on TT maturation pathways. We propose that TTs undergo ordered developmental phases, each representing a learning cycle that we call Formation, Knowledge Generation, and Translation. We identify major activities of each phase linked to development goals. Transition to subsequent phases is associated with a team learning cycle, resulting in adaptations that enabling progression towards clinical translation. We present known antecedents of stage-dependent competencies and rubrics for their assessment. Application of this model will ease assessment, facilitate goal identification and align relevant training interventions to improve performance of TTs in the CTSA context.

Predicting Norovirus in England Using Existing and Emerging Syndromic Data: Infodemiology Study.

BACKGROUND: Norovirus is associated with approximately 18% of the global burden of gastroenteritis and affects all age groups. There is currently no licensed vaccine or available antiviral treatment. However, well-designed early warning systems and forecasting can guide nonpharmaceutical approaches to norovirus infection prevention and control. OBJECTIVE: This study evaluates the predictive power of existing syndromic surveillance data and emerging data sources, such as internet searches and Wikipedia page views, to predict norovirus activity across a range of age groups across England. METHODS: We used existing syndromic surveillance and emerging syndromic data to predict laboratory data indicating norovirus activity. Two methods are used to evaluate the predictive potential of syndromic variables. First, the Granger causality framework was used to assess whether individual variables precede changes in norovirus laboratory reports in a given region or an age group. Then, we used random forest modeling to estimate the importance of each variable in the context of others with two methods: (1) change in the mean square error and (2) node purity. Finally, these results were combined into a visualization indicating the most influential predictors for norovirus laboratory reports in a specific age group and region. RESULTS: Our results suggest that syndromic surveillance data include valuable predictors for norovirus laboratory reports in England. However, Wikipedia page views are less likely to provide prediction improvements on top of Google Trends and Existing Syndromic Data. Predictors displayed varying relevance across age groups and regions. For example, the random forest modeling based on selected existing and emerging syndromic variables explained 60% variance in the ≥65 years age group, 42% in the East of England, but only 13% in the South West region. Emerging data sets highlighted relative search volumes, including "flu symptoms," "norovirus in pregnancy," and norovirus activity in specific years, such as "norovirus 2016." Symptoms of vomiting and gastroenteritis in multiple age groups were identified as important predictors within existing data sources. CONCLUSIONS: Existing and emerging data sources can help predict norovirus activity in England in some age groups and geographic regions, particularly, predictors concerning vomiting, gastroenteritis, and norovirus in the vulnerable populations and historical terms such as stomach flu. However, syndromic predictors were less relevant in some age groups and regions likely due to contrasting public health practices between regions and health information-seeking behavior between age groups. Additionally, predictors relevant to one norovirus season may not contribute to other seasons. Data biases, such as low spatial granularity in Google Trends and especially in Wikipedia data, also play a role in the results. Moreover, internet searches can provide insight into mental models, that is, an individual's conceptual understanding of norovirus infection and transmission, which could be used in public health communication strategies.

The relationship between grammatical knowledge and reading comprehension: A meta-analysis.

The study aimed to examine the cohesive tie effect on reading comprehension through the grammatical knowledge cognition process. The present meta-analysis examined the correlation between grammatical knowledge and reading comprehension based on empirical results published between 1998 and 2021. This study selected 86 studies with a total of 14,852 readers whose grades were grouped from primary school to university. The results showed that the overall correlation effect size between grammatical knowledge and reading comprehension was large, and the significant interaction effect of the grade group was confirmed through moderator analysis. The results suggested that the grammatical knowledge's function of the cohesive tie has a transfer effect across different text comprehension scripts.

Mental representation of climate-relevant behaviours: Confirmatory testing of similarity patterns obtained in a card sorting task by young adults.

Efforts to promote climate-friendly consumption need to address groups of interrelated behaviours; however, experts and laypeople have different perspectives on which climate-relevant behaviours belong together. Understanding laypeople's mental representations, or the perceived similarity of behaviours, may provide orientation on which behaviours should be promoted in concert in order to communicate comprehensibly and to catalyse spillover. The present study uses data on perceived similarity between 22 climate-relevant behaviours collected from 413 young adults in Austria in an open card sorting task. Five posited categorisations by domain, location, impact, difficulty, and frequency are tested in a confirmatory approach for their fit with the observed similarity patterns. By analysing co-occurrence matrices, edit distances and similarity indices, the best fit is found for the null hypothesis of random assignment. Ranking by test statistics shows that the domain categorisation fits next best, followed by impact, frequency, difficulty, and location. The categories of waste and advocacy behaviours emerge consistently in lay mental representations. The categories of behaviours with a high carbon footprint and difficult behaviours that are performed by few other people stand out from other, less extreme behaviours. Categorisation fit is not moderated by personal norms, stated competencies, and environmental knowledge. The analytical approaches for confirmatory testing of expected categorisations against observed similarity patterns may be applied to analyse any card sorting data.

A 3D mixed reality visualization of network topology and activity results in better dyadic cyber team communication and cyber situational awareness.

Background: Cyber defense decision-making during cyber threat situations is based on human-to-human communication aiming to establish a shared cyber situational awareness. Previous studies suggested that communication inefficiencies were among the biggest problems facing security operation center teams. There is a need for tools that allow for more efficient communication of cyber threat information between individuals both in education and during cyber threat situations. Methods: In the present study, we compared how the visual representation of network topology and traffic in 3D mixed reality vs. 2D affected team performance in a sample of cyber cadets (N = 22) cooperating in dyads. Performance outcomes included network topology recognition, cyber situational awareness, confidence in judgements, experienced communication demands, observed verbal communication, and forced choice decision-making. The study utilized network data from the NATO CCDCOE 2022 Locked Shields cyber defense exercise. Results: We found that participants using the 3D mixed reality visualization had better cyber situational awareness than participants in the 2D group. The 3D mixed reality group was generally more confident in their judgments except when performing worse than the 2D group on the topology recognition task (which favored the 2D condition). Participants in the 3D mixed reality group experienced less communication demands, and performed more verbal communication aimed at establishing a shared mental model and less communications discussing task resolution. Better communication was associated with better cyber situational awareness. There were no differences in decision-making between the groups. This could be due to cohort effects such as formal training or the modest sample size. Conclusion: This is the first study comparing the effect of 3D mixed reality and 2D visualizations of network topology on dyadic cyber team communication and cyber situational awareness. Using 3D mixed reality visualizations resulted in better cyber situational awareness and team communication. The experiment should be repeated in a larger and more diverse sample to determine its potential effect on decision-making.

Distributed team processes in healthcare services: a scoping review.

Objective: High-quality healthcare services is delivered by teams rather than individuals and depends heavily on multidisciplinary cooperation between dispersed healthcare professionals. The aim of this scoping review is to identify common barriers and innovative applications of technology supporting team processes and patient safety, in geographically dispersed healthcare services. Methods: Studies were identified from searches in APA PsychINFO, Epistemonikos and Medline databases, from 2010 to 2023. A detailed search strategy was performed, and studies were included, based on prior established criteria. Results: Among the 19 studies that fulfilled our inclusion criteria, the majority (85%) were from Europe or North America, and most studies (53%) were quantitative, with a cross-sectional study design. Several reported observed distributed team processes in training and education. Most studies described barriers and detailed how innovative approaches and technological solutions were introduced to improve communication, coordination, and shared mental models in distributed healthcare settings. A small proportion of studies (16%) used health services data to examine interpersonal exchange and team processes. Conclusion: The scoping review offer recommendations to enhance future research on distributed team processes in healthcare services.

Communication and cooperation within a stroke rehabilitation team: a qualitative research / 中国康复理论与实践

ObjectiveTo explore the obstacles and causes of communication and cooperation among doctors, nurses and rehabilitation therapists in a stroke rehabilitation team. MethodsFrom July to October, 2022, twelve rehabilitation evaluation meetings were observed using ethnographic research, based on Shared Mental Model theory. Semi-structured interviews were held with five doctors, ten nurses and four rehabilitation therapists. ResultsFour themes and nine sub-themes were presented, namely equipment (poor interoperability of information system, limited knowledge of rehabilitation equipment for doctors and nurses), task (members were under time pressure to attend meeting, imperfect inter-discipline communication system), team interaction (insufficient information sharing, unfamiliar with roles/responsibilities, misunderstanding between specialties) and team member (less participation of nurses, limited multidisciplinary knowledge). ConclusionThe communication and cooperation among stroke rehabilitation team members is limited by many factors, such as equipment, task, team interaction and team members. It is suggested to improve interoperability of information systems, create a supportive environment, know each other's roles/responsibilities, strengthen interdisciplinary crossover, pay attention to and support the cultivation of nurses' ability, to promote efficient communication and cooperation among team members.